This is the third in a series of pieces I’m writing around future technology, the innovations that we are seeing, and the impact that it will have around organisational learning and performance. There are seven aspects of innovation that I’m considering: technologies that filter, technologies that connect, augmentation, artificial intelligence, sense making technologies, temperature checks, and the creation of audioscapes. Today I want to consider temperature checks: the ability to rapidly, or even synchronously, take a measurement across a social system.

Organisations have historically been terribly bad at measuring the temperature: is not uncommon that I go into organisations which carry out an annual engagement survey and publish the results eight months later. By no stretch of the imagination does this count as taking the temperature before the patient has died. Even the move towards monthly engagement scores is just the start: the real disruption will come from the ability of new technologies to measure often, to measure broadly, and to synthesise results holistically.

Temperature check types of technology invariably seem to be tied into mobile: the ability to push questions out to populations and ask for a rapid, and crucially simple, response. These are not long surveys, and nor will they require logging on to dedicated systems. Most likely they require micro-engagement, cognitive surplus, aggregated up to the organisational itself. What will we measure?

Happiness is an easy place to start: imagine measuring every day if people are happy. Or more specifically, are you happier, or less happy, than you were yesterday. This may seem trivial, but consider the trends: do people simply bounce around all over the place, or are we able to measure? And, if we can measure, what can we learn? Happiness is easy, what about measuring other things: we have the ability to synchronously measure engagement in collaborative spaces. I wonder if that relates to happiness? And fairness. Using simple temperature check software, we can gain a sense of how fair people feel the organisation is, or even how fairly specific situations have been handled.

Again, this may sound pointless, but consider this: in the Landscape of Trust research that I’m currently carrying out, 50% of people believe that the organisation sometimes or often exploits them, and 54% of people have low or no trust in the organisation that they work for. These are not strong results: our ability to affect marginal gains in this space can directly contribute to the organisation being more Socially Dynamic.

We are becoming highly adept at measuring the amplification and certain social channels, but we are likely to see a greater ability to aggregate these results and, crucially, interpret them to provide meaningful feedback on how stories are shaped and shared. Again, this will tie into applications of artificial intelligence: performance support bots that can provide contextual feedback as we write and craft our stories.

In the Social Age we have seen the widespread democratisation of creativity as tools have become simpler to use and cheaply available: we are not yet measuring the impacts of this within an organisation, but imagine temperature checks around creativity. When an organisation lacks innovation, does it also lack creativity? Or when people are happier, are they more creative? Or when trust is higher, are they more creative?

Through various wearable technologies, we are already seeing the ability to quantify exercise and rest, as well as the quality of sleep, and we are seeing the aggregation of this into other types of data, for example the ability now to measure how lorry drivers are performing, when they are resting, how heavily they are braking, their average speed, and deduce from this how rested and capable they are at a given moment. There are even efforts afoot to tie this into an understanding of how stressful different parts of the road network are, on the basis that if we understand how rested drivers are, and how dangerous particular stretches of road are, we can modify driving schedules accordingly, or even determined that certain drivers are more capable of certain types of road.

Temperature checks should enable us to create benchmarks to pinpoint which facets of organisational operation require attention: this may tie into resilience itself, understanding how the Socially Dynamic organisation is resilient through a diversified strength, but crucially, a strength that it understands. If temperature checks and meta-analysis between different measures can give us that understanding, and if we can tie this into machine learning based refinement of activities, we can become more responsive and more resilient.

A problem does exist that we are very familiar with: measuring somethings is easy, so they tend to be measured, whilst other things are hard, so they are ignored. It’s easy to measure something like happiness, but remarkably difficult to measure something like fairness, and yet our ability to innovate around methodologies may allow us to do so, and our ability to innovate around technology may allow us to make meaningful interventions based upon this.

We are not looking for levers of power: the ability to measure something doesn’t mean we can easily impact upon it. That type of mechanistic thinking and constructivist approach carries great risk, and is likely that vendor’s will exploit this risk, indicating that our ability to deliver more synchronous measurement will somehow innately indicate our ability to do something with that knowledge, whilst in truth, it is a mindset change that is required. That, and a lot of learning.

There is a vision of the future of organisations with a certain type of buffered resilience: the ability of systems to learn and react to the performance and well-being of the individual, and to the performance and well-being of the community is a whole. Temperature checks will doubtless be a key part of the array of measurements that will enable this to happen.